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mlpack compilation fails when LAPACK is not found by cmake. One solutions is to enable mlpack’s CMakeLists.txt to find LAPACK. Namely, the solution is to add FindLAPACK.cmake in the directory mlpack-1.0.9/CMake so that cmake can find LAPACK.

mlpack::gmm::Estimate() estimates the probability distribution directly from the given observations, using the given algorithm in the FittingType class to fit the data. The fitting will be performed ‘trials’ times; from these trials, the model with the greatest log-likelihood will be selected. By default, only one trial is performed. The log-likelihood of the best fitting is returned.

template<typename FittingType = EMFit<>>
double mlpack::gmm::GMM< FittingType >::Estimate(
const arma::mat & observations, // Observations of the model.
const size_t trials = 1, // Number of trials to perform; the model in these trials with the greatest log-likelihood will be selected.
const bool useExistingModel = false // If true, the existing model is used as an initial model for the estimation.
)

taking into account the probability of each observation actually being from this distribution

template<typename FittingType = EMFit<>>
double mlpack::gmm::GMM< FittingType >::Estimate(
const arma::mat & observations, // Observations of the model.
const arma::vec & probabilities, // Probability of each observation being from this distribution.
const size_t trials = 1, // Number of trials to perform; the model in these trials with the greatest log-likelihood will be selected.
const bool useExistingModel = false // If true, the existing model is used as an initial model for the estimation.
)

Create a GMM with the given number of Gaussians, each of which have the specified dimensionality.
Also, pass in an initialized FittingType class; this is useful in cases where the FittingType class needs to store some state.

mlpack is a C++ machine learning library, which is developed by the fundamental algorithmic and statistical tools laboratory (FASTLab) at Georgia Tech. Machine learning methods implemented in mlpack are following: